This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low ...This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low resolution thermal infrared imaging,various optimizations have been carried out to improve the speed and accuracy of thermal infrared 3D reconstruction.Firstly,inspired by Boltzmann's law of thermal radiation,distance is incorporated into the NeRF model for the first time,resulting in a nonlinear propagation of a single ray and a more accurate description of the physical property that infrared radiation intensity decreases with increasing distance.Secondly,in terms of improving inference speed,based on the phenomenon of high and low frequency distribution of foreground and background in infrared images,a multi ray non-uniform light synthesis strategy is proposed to make the model pay more attention to foreground objects in the scene,reduce the distribution of light in the background,and significantly reduce training time without reducing accuracy.In addition,compared to visible light scenes,infrared images only have a single channel,so fewer network parameters are required.Experiments using the same training data and data filtering method showed that,compared to the original NeRF,the improved network achieved an average improvement of 13.8%and 4.62%in PSNR and SSIM,respectively,while an average decreases of 46%in LPIPS.And thanks to the optimization of network layers and data filtering methods,training only takes about 25%of the original method's time to achieve convergence.Finally,for scenes with weak backgrounds,this article improves the inference speed of the model by 4-6 times compared to the original NeRF by limiting the query interval of the model.展开更多
0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donz...0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donzé,2012;Jiang et al.,2009;Pine et al.,2006;Aydan et al.,1989).展开更多
0 INTRODUCTION Geohazards in mountainous regions pose significant risks to the construction and safe operation of transportation,water conservancy,and other critical infrastructure projects.Engineering geological inve...0 INTRODUCTION Geohazards in mountainous regions pose significant risks to the construction and safe operation of transportation,water conservancy,and other critical infrastructure projects.Engineering geological investigations are crucial for disaster prevention and mitigation.展开更多
This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,an...This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.展开更多
Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT...Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.展开更多
Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009-2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manual...Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009-2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts （ECMWF） analyses. The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are -1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions （air temperature 〈 -10~C） also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.展开更多
The stability of cemented backfill mass is important to keep miners and equipment safe in underground backfill miming.The stress-strain behavior, resistivity and thermal infrared(TIR) characteristics of backfill mass ...The stability of cemented backfill mass is important to keep miners and equipment safe in underground backfill miming.The stress-strain behavior, resistivity and thermal infrared(TIR) characteristics of backfill mass under uniaxial compression were investigated. The monitoring system consisted of a TIR observation system, a stress-strain monitoring system and a resistivity measurement system. Precursory information for impending failure of cemented backfill mass was collected, including TIR, strain and resistivity precursors. The sensitivity and difference of different monitoring information to the same failure event were compared.The results show that the time-space evolution process of the resistivity and TIR is basically the same as the whole process from compression deformation to failure of backfill mass, and the time variation of resistivity and TIR is obviously characterized by stage.The resistivity precursor turns out earlier than the TIR and the strain. The resistivity relation with loading compression is anti-symmetry, decreasing as the compression stress increases before the peak strength of backfill mass. However, when the backfill mass enters into the phase of failure, the resistivity starts to increase as the stress increases. The change of the resistivity growth direction can be regarded as the resistivity-caution-point for the failure of backfill mass under uniaxial compression. It is also indicated that the TIR information mainly represents the surface temperature evolution in the process of compression before the backfill enters into the plastic-yield state. It can be a valuable tool to obtain the precursors for failure of cemented backfill mass for backfill mines.展开更多
The present paper utilizes thermal infrared image for inversion of winter wheat yield and biomass with different technology of irrigation(drip irrigation,sprinkler irrigation,flood irrigation).It is the first time tha...The present paper utilizes thermal infrared image for inversion of winter wheat yield and biomass with different technology of irrigation(drip irrigation,sprinkler irrigation,flood irrigation).It is the first time that thermal infrared image is used for predicting the winter wheat yield and biomass.The temperature of crop and background was measured by thermal infrared image.It is necessary to get the crop background separation index(CBSIL,CBSIH),which can be used for distinguishing the crop value from the image.CBSIL and CBSIH(the temperature when the leaves are wet adequately;the temperature when the stomata of leaf is closed completely) are the threshold values.The temperature of crop ranged from CBSIL to CBSIH.Then the ICWSI was calculated based on relevant theoretical method.The value of stomata leaf has strong negative correlation with ICWSI proving the reliable value of ICWSI.In order to construct the high accuracy simulation model,the samples were divided into two parts.One was used for constructing the simulation model,the other for checking the accuracy of the model.Such result of the model was concluded as:(1) As for the simulation model of soil moisture,the correlation coefficient(R2) is larger than 0.887 6,the average of relative error(Er) ranges from 13.33% to 16.88%;(2) As for the simulation model of winter wheat yield,drip irrigation(0.887 6,16.89%,-0.12),sprinkler irrigation(0.970 0,14.85%,-0.12),flood irrigation(0.969 0,18.87%,0.18),with the values of R2,Er and CRM listed in the parentheses followed by the individual term.(3) As for winter wheat biomass,drip irrigation(0.980 0,13.70%,0.13),sprinkler irrigation(0.95,13.15%,-0.14),flood irrigation(0.970 0,14.48%,-0.13),and the values in the parentheses are demonstrated the same as above.Both the CRM and Er are shown to be very low values,which points to the accuracy and reliability of the model investigated.The accuracy of model is high and reliable.The results indicated that thermal infrared image can be used potentially for inversion of winter wheat yield and biomass.展开更多
Based on an interpretation and study of the satellite remote-sensing images of FY-2C thermal infrared 1st wave band （10.3-11.3 μm） designed in China, the authors found that there existed obvious and isolated satell...Based on an interpretation and study of the satellite remote-sensing images of FY-2C thermal infrared 1st wave band （10.3-11.3 μm） designed in China, the authors found that there existed obvious and isolated satellite thermal infrared anomalies before the 5.12 Wenchuan Ms 8.0 Earthquake. These anomalies had the following characteristics： （1） The precursor appeared rather early： on March 18, 2008, i.e., 55 days before the earthquake, thermal infrared anomalies began to occur; （2） The anomalies experienced quite many and complex evolutionary stages： the satellite thermal infrared anomalies might be divided into five stages, whose manifestations were somewhat different from each other. The existence of so many anomaly stages was probably observed for the first time in numerous cases of satellite thermal infrared research on earthquakes; （3） Each stage lasted quite a long time, with the longest one spanning 13 days; （4） An evident geothermal anomaly gradient was distributed along the Longmen seismic fracture zone, and such a phenomenon might also be discovered for the first time in satellite thermal infrared earthquake research. This discovery is therefore of great guiding and instructive significance in the study of the earthquake occurrence itself and the trend of the postearthquake phenomena.展开更多
Longwall mining continues to remain the most efficient method for underground coal recovery. A key aspect in achieving safe and productive longwall mining is to ensure that the shearer is always correctly positioned w...Longwall mining continues to remain the most efficient method for underground coal recovery. A key aspect in achieving safe and productive longwall mining is to ensure that the shearer is always correctly positioned within the coal seam. At present, this machine positioning task is the role of longwall personnel who must simultaneously monitor the longwall coal face and the shearer's cutting drum position to infer the geological trends of the coal seam. This is a labour intensive task which has negative impacts on the consistency and quality of coal production. As a solution to this problem, this paper presents a sensing method to automatically track geological coal seam features on the longwall face, known as marker bands, using thermal infrared imaging. These non-visible marker bands are geological features that link strongly to the horizontal trends present in layered coal seams. Tracking these line-like features allows the generation of a vertical datum that can be used to maintain the shearer in a position for optimal coal extraction. Details on the theory of thermal infrared imaging are given, as well as practical aspects associated with machine-based implementation underground. The feature detection and tracking tasks are given with real measurements to demonstrate the efficacy of the approach. The outcome is important as it represents a new selective mining capability to help address a long-standing limitation in longwall mining operations.展开更多
The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which ...The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR （visible and near infrared） data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM （genetic algorithms ＆ self-organizing feature maps）-ANN （artificial neural net-work）. Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision.展开更多
Co-seismic gas leakage usually occurs on the edge of seismic faults in petroliferous basins,and it may have an impact on the local environment,such as the greenhouse effect,which can cause thermal infrared brightness ...Co-seismic gas leakage usually occurs on the edge of seismic faults in petroliferous basins,and it may have an impact on the local environment,such as the greenhouse effect,which can cause thermal infrared brightness anomalies.Using wavelet transform and power spectrum estimation methods,we processed brightness temperature data from the Chinese geostationary meteorological satellite FY-C/E.We report similarities between the co-seismic thermal infrared brightness(CTIB)anomalies before,during and after earthquakes that occurred at the edges of the Sichuan,Tarim,Qaidam,and Junggar basins surrounding the North and East of the Qinghai–Tibet Plateau in western China.Additionally,in each petroliferous basin,the area of a single CTIB anomaly accounted for 50%to 100%of the basin area,and the spatial distribution similarities in the CTIB anomalies existed before,during and after these earthquakes.To better interpret the similarities,we developed a basin warming effect model based on geological structures and topography.The model suggests that in a petroliferous basin with a subsurface gas reservoir,gas leakage could strengthen with the increasing stress before,during,and even after an earthquake.The accumulation of these gases,such as the greenhouse gases CH4 and CO2,results in the CTIB anomalies.In addition,we conclude that the CTIB anomalies are strengthened by the high mountains(altitude^5000 m)around the basins and the basins’independent climatic conditions.This work provides a new perspective from which to understand the CTIB anomalies in petroliferous basins surrounding the North and East of the Qinghai–Tibet Plateau.展开更多
According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under...According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under the domain of neighborhood wavelet reconstruction, data of TM and MO DIS are divided into three layers using wavelet decomposition. The texture information of TM data is retained by fusing highfrequency information. The neighborhood correction coefficient method （NC CM） is set up based on the search neighborhood of a certain size to fuse lowfrequency information. Thermal infrared value of MODIS data is reduced to the space value of TM data by applying NCCM. The data with high spectrum, high spatial and high temporal resolution, are obtained through the al gorithm in the paper. Verification results show that the texture information of TM data and high spec tral information of MODIS data could be preserved well by the fusion algorithm. This article could provide technical support for high precision and fast extraction of the surface environment parame ters.展开更多
This paper used the thermal infrared data of the satellite NOAA-AAVHRR of the north pat of North China (113°~119°E, 38°~42°N), and processed the remote sensing data through radiation adjustment, ge...This paper used the thermal infrared data of the satellite NOAA-AAVHRR of the north pat of North China (113°~119°E, 38°~42°N), and processed the remote sensing data through radiation adjustment, geometric adjust ment and so on by the software 'The Monitoring and Fast Process System of Earthquake Precursor Thermal Infra red Anomaly', inversed the each surface temperature. Some disturbances effect had been excluded, and thermal infrared temperature anomaly had been extracted by the picture difference method. The Zhangbei M_s=6.2 earth quake is used as the example in the paper, so that in the paper thermal infrared characteristics on time-space before earthquake and the relationship between the anomaly and the earthquake prediction have been summarized. Within more than ten days before the Zhangbei earthquake, the thermal infrared anomaly had emerged widely along Zhangjiakou-Bobal seismic belt, and the anomalous region seemed like a belt and it is also consistent with the tectonic background there; the anomaly expanded from the outside toward the earthquake focus, but the focus lay at the edge of the thermal infrared region. So it is possible to explore a new anomaly observation method for earthquake prediction by observing and studying the satellite thermal infrared anomaly before big earthquakes happen.展开更多
The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal in...The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal infrared images. Six diagnostic indicators for the prediction of global earthquakes with magnitude ≥6.0 and their quantitative evaluation standards have been established. The microscopic behavior of global crustal movement is successfully controlled by using satellite thermal infrared imagery, and the occurrence time and magnitude of over 80% of global strong earthquakes occurred since the foundation of the observation station have been successfully predicted. It is believed that the combination of satellite thermal infrared information with macroscopic anomalous phenomena will play an important role in earthquake hazard reduction.展开更多
Aiming at two Dayao earthquakes with magnitude more than 6 occurred in 2003 in Yunnan Province, we analyzed and interpreted the NOAA satellite thermal infrared images of 1999, 2003 and 2004 in Chuandian region, and al...Aiming at two Dayao earthquakes with magnitude more than 6 occurred in 2003 in Yunnan Province, we analyzed and interpreted the NOAA satellite thermal infrared images of 1999, 2003 and 2004 in Chuandian region, and also calculated the annual variation of brightness temperature of the hot belt along Honghe fault to explore the formation cause of the high temperature belt and its relation to the earthquakes. The results show that the high temperature belt along Honghe fault is caused by geographic environment factors, such as water system and terrain. But the annual average brightness temperature of the belt in earthquake year of 2003 is clearly higher than that in no earthquake years of 1999 and 2004, this maybe indicates that the thermal activities of Honghe fault increase in earthquake years, and can cause the annual variation anomaly of brightness temperature. We can detect and monitor this thermal activities of Honghe fault before earthquake by analyzing and comparing the relative changes of thermal infrared brightness temperature of the hot belt in different years.展开更多
Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for...Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.展开更多
Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.H...Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.展开更多
Rockfalls are among the frequent hazards in underground mines worldwide,requiring effective methods for detecting unstable rock blocks to ensure miners’and equipment’s safety.This study proposes a novel approach for...Rockfalls are among the frequent hazards in underground mines worldwide,requiring effective methods for detecting unstable rock blocks to ensure miners’and equipment’s safety.This study proposes a novel approach for identifying potential rockfall zones using infrared thermal imaging and image segmentation techniques.Infrared images of rock blocks were captured at the Draa Sfar deep underground mine in Morocco using the FLUKE TI401 PRO thermal camera.Two segmentation methods were applied to locate the potential unstable areas:the classical thresholding and the K-means clustering model.The results show that while thresholding allows a binary distinction between stable and unstable areas,K-means clustering is more accurate,especially when using multiple clusters to show different risk levels.The close match between the clustering masks of unstable blocks and their corresponding visible light images further validated this.The findings confirm that thermal image segmentation can serve as an alternative method for predicting rockfalls and monitoring geotechnical issues in underground mines.Underground operators worldwide can apply this approach to monitor rock mass stability.However,further research is recommended to enhance these results,particularly through deep learning-based segmentation and object detection models.展开更多
Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.Ho...Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.However,observing sleeping sites at night is challenging,especially for species sensitive to human disturbance.Thermal infrared imaging(TIR)with drones is increasingly used for detecting and counting primates,yet it has not been utilized to investigate ecological strategies.This study investigates the sleeping site selection of the Critically Endangered black-shanked douc langur(Pygathrix nigripes)in Cát Tiên National Park,Vietnam.Our aim is to assess the feasibility of using a TIR drone to test sleeping site selection strategies in non-nesting primates,specifically examining hypotheses related to predation avoidance and food proximity.Between January and April 2023,we conducted 120 drone flights along 22 transects(~1-km long)and identified 114 sleeping sites via thermal imaging.We established 116 forest structure plots along 29 transects in non-selected sites and 65 plots within douc langur sleeping sites.Our observations reveal that douc langurs selected tall and large trees that may provide protection against predators.Additionally,they selected sleeping sites with increased access to food,such as Afzelia xylocarpa,which serves as a preferred food source during the dry season.These results highlight the effective use of TIR drones for studying douc langur sleeping site selection with minimal disturbance.Besides offering valuable insights into habitat selection and behavioral ecology for conservation,TIR drones hold great promise for the noninvasive and long-term monitoring of large-bodied arboreal species.展开更多
基金Support by the Fundamental Research Funds for the Central Universities(2024300443)the National Natural Science Foundation of China(NSFC)Young Scientists Fund(62405131)。
文摘This article proposes a three-dimensional light field reconstruction method based on neural radiation field(NeRF)called Infrared NeRF for low resolution thermal infrared scenes.Based on the characteristics of the low resolution thermal infrared imaging,various optimizations have been carried out to improve the speed and accuracy of thermal infrared 3D reconstruction.Firstly,inspired by Boltzmann's law of thermal radiation,distance is incorporated into the NeRF model for the first time,resulting in a nonlinear propagation of a single ray and a more accurate description of the physical property that infrared radiation intensity decreases with increasing distance.Secondly,in terms of improving inference speed,based on the phenomenon of high and low frequency distribution of foreground and background in infrared images,a multi ray non-uniform light synthesis strategy is proposed to make the model pay more attention to foreground objects in the scene,reduce the distribution of light in the background,and significantly reduce training time without reducing accuracy.In addition,compared to visible light scenes,infrared images only have a single channel,so fewer network parameters are required.Experiments using the same training data and data filtering method showed that,compared to the original NeRF,the improved network achieved an average improvement of 13.8%and 4.62%in PSNR and SSIM,respectively,while an average decreases of 46%in LPIPS.And thanks to the optimization of network layers and data filtering methods,training only takes about 25%of the original method's time to achieve convergence.Finally,for scenes with weak backgrounds,this article improves the inference speed of the model by 4-6 times compared to the original NeRF by limiting the query interval of the model.
基金supported by the National Key R&D Program of China(No.2022YFC3080200)。
文摘0 INTRODUCTION Rock masses are inherently discontinuous,with fractures and joints governing their mechanical behavior and stability(Liu et al.,2024;Shang et al.,2018;Lisjak and Grasselli,2014;Scholtès and Donzé,2012;Jiang et al.,2009;Pine et al.,2006;Aydan et al.,1989).
基金financially supported by the National Key R&D Program of China(No.2022YFC3080200)。
文摘0 INTRODUCTION Geohazards in mountainous regions pose significant risks to the construction and safe operation of transportation,water conservancy,and other critical infrastructure projects.Engineering geological investigations are crucial for disaster prevention and mitigation.
基金Supported by the Fundamental Research Funds for the Central Universities(2024300443)the Natural Science Foundation of Jiangsu Province(BK20241224).
文摘This paper presents a high-speed and robust dual-band infrared thermal camera based on an ARM CPU.The system consists of a low-resolution long-wavelength infrared detector,a digital temperature and humid⁃ity sensor,and a CMOS sensor.In view of the significant contrast between face and background in thermal infra⁃red images,this paper explores a suitable accuracy-latency tradeoff for thermal face detection and proposes a tiny,lightweight detector named YOLO-Fastest-IR.Four YOLO-Fastest-IR models(IR0 to IR3)with different scales are designed based on YOLO-Fastest.To train and evaluate these lightweight models,a multi-user low-resolution thermal face database(RGBT-MLTF)was collected,and the four networks were trained.Experiments demon⁃strate that the lightweight convolutional neural network performs well in thermal infrared face detection tasks.The proposed algorithm outperforms existing face detection methods in both positioning accuracy and speed,making it more suitable for deployment on mobile platforms or embedded devices.After obtaining the region of interest(ROI)in the infrared(IR)image,the RGB camera is guided by the thermal infrared face detection results to achieve fine positioning of the RGB face.Experimental results show that YOLO-Fastest-IR achieves a frame rate of 92.9 FPS on a Raspberry Pi 4B and successfully detects 97.4%of faces in the RGBT-MLTF test set.Ultimate⁃ly,an infrared temperature measurement system with low cost,strong robustness,and high real-time perfor⁃mance was integrated,achieving a temperature measurement accuracy of 0.3℃.
基金the National Natural Science Foundation(No.52073187)NSAF Foundation(No.U2230202)for their financial support of this project+3 种基金National Natural Science Foundation(No.51721091)Programme of Introducing Talents of Discipline to Universities(No.B13040)State Key Laboratory of Polymer Materials Engineering(No.sklpme2022-2-03)support of China Scholarship Council
文摘Pre-polymerized vinyl trimethoxy silane(PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization,sol-gel transition and supercritical CO_(2)drying.The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size(30-40 nm),high specific surface area(559 m^(2)g^(−1)),high void fraction(91.7%)and enhanced mechanical property:(1)the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect(beneficial for infrared(IR)stealth);(2)the heterogeneous interface was beneficial for IR reflection(beneficial for IR stealth)and MWCNT polarization loss(beneficial for electromagnetic wave(EMW)attenuation);(3)the high void fraction was beneficial for enhancing thermal insulation(beneficial for IR stealth)and EMW impedance match(beneficial for EMW attenuation).Guided by the above theoretical design strategy,PVTMS@MWCNT nano-aerogel shows superior EMW absorption property(cover all Ku-band)and thermal IR stealth property(ΔT reached 60.7℃).Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity,an extremely high electromagnetic interference shielding material(66.5 dB,2.06 mm thickness)with superior absorption performance of an average absorption-to-reflection(A/R)coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz(A/R ratio more than 10)was experimentally obtained in this work.
基金The Chinese Polar Environment Comprehensive Investigation&Assessment Programs under contract No.CHINARE-02-04the International Science and Technology Cooperation Project of China under contract No.2011DFA22260+3 种基金the Open Research Fund of Key Laboratory of Digital Earth Science,Institute of Remote Sensing and Digital Earth,Chinese Academy of Sciences under contract No.2014LDE009the Public Science and Technology Research Funds Projects of Ocean under contract No.201105016the Academy of Finland under contract No.259537the National Natural Science Foundation of China under contract No.41428603
文摘Level ice thickness distribution pattern in the Bohai Sea in the winter of 2009-2010 was investigated in this paper using MODIS night-time thermal infrared imagery. The cloud cover in the imagery was masked out manually. Level ice thickness was calculated using MODIS ice surface temperature and an ice surface heat balance equation. Weather forcing data was from the European Centre for Medium-Range Weather Forecasts （ECMWF） analyses. The retrieved ice thickness agreed reasonable well with in situ observations from two off-shore oil platforms. The overall bias and the root mean square error of the MODIS ice thickness are -1.4 cm and 3.9 cm, respectively. The MODIS results under cold conditions （air temperature 〈 -10~C） also agree with the estimated ice growth from Lebedev and Zubov models. The MODIS ice thickness is sensitive to the changes of the sea ice and air temperature, in particular when the sea ice is relatively thin. It is less sensitive to the wind speed. Our method is feasible for the Bohai Sea operational ice thickness analyses during cold freezing seasons.
基金Projects(51504256,51004109)supported by the National Natural Science Foundation of ChinaProject(zdsys006)supported by State Key Laboratory of Safety and Health for Metal Mines,ChinaProject(2013BAB02B04)supported by the National Science and Technology Support Plan,China
文摘The stability of cemented backfill mass is important to keep miners and equipment safe in underground backfill miming.The stress-strain behavior, resistivity and thermal infrared(TIR) characteristics of backfill mass under uniaxial compression were investigated. The monitoring system consisted of a TIR observation system, a stress-strain monitoring system and a resistivity measurement system. Precursory information for impending failure of cemented backfill mass was collected, including TIR, strain and resistivity precursors. The sensitivity and difference of different monitoring information to the same failure event were compared.The results show that the time-space evolution process of the resistivity and TIR is basically the same as the whole process from compression deformation to failure of backfill mass, and the time variation of resistivity and TIR is obviously characterized by stage.The resistivity precursor turns out earlier than the TIR and the strain. The resistivity relation with loading compression is anti-symmetry, decreasing as the compression stress increases before the peak strength of backfill mass. However, when the backfill mass enters into the phase of failure, the resistivity starts to increase as the stress increases. The change of the resistivity growth direction can be regarded as the resistivity-caution-point for the failure of backfill mass under uniaxial compression. It is also indicated that the TIR information mainly represents the surface temperature evolution in the process of compression before the backfill enters into the plastic-yield state. It can be a valuable tool to obtain the precursors for failure of cemented backfill mass for backfill mines.
基金China-Germany international cooperation project(IRTG1070)National Natural Science Foundation of China(Item number:0971940)
文摘The present paper utilizes thermal infrared image for inversion of winter wheat yield and biomass with different technology of irrigation(drip irrigation,sprinkler irrigation,flood irrigation).It is the first time that thermal infrared image is used for predicting the winter wheat yield and biomass.The temperature of crop and background was measured by thermal infrared image.It is necessary to get the crop background separation index(CBSIL,CBSIH),which can be used for distinguishing the crop value from the image.CBSIL and CBSIH(the temperature when the leaves are wet adequately;the temperature when the stomata of leaf is closed completely) are the threshold values.The temperature of crop ranged from CBSIL to CBSIH.Then the ICWSI was calculated based on relevant theoretical method.The value of stomata leaf has strong negative correlation with ICWSI proving the reliable value of ICWSI.In order to construct the high accuracy simulation model,the samples were divided into two parts.One was used for constructing the simulation model,the other for checking the accuracy of the model.Such result of the model was concluded as:(1) As for the simulation model of soil moisture,the correlation coefficient(R2) is larger than 0.887 6,the average of relative error(Er) ranges from 13.33% to 16.88%;(2) As for the simulation model of winter wheat yield,drip irrigation(0.887 6,16.89%,-0.12),sprinkler irrigation(0.970 0,14.85%,-0.12),flood irrigation(0.969 0,18.87%,0.18),with the values of R2,Er and CRM listed in the parentheses followed by the individual term.(3) As for winter wheat biomass,drip irrigation(0.980 0,13.70%,0.13),sprinkler irrigation(0.95,13.15%,-0.14),flood irrigation(0.970 0,14.48%,-0.13),and the values in the parentheses are demonstrated the same as above.Both the CRM and Er are shown to be very low values,which points to the accuracy and reliability of the model investigated.The accuracy of model is high and reliable.The results indicated that thermal infrared image can be used potentially for inversion of winter wheat yield and biomass.
基金support from the Key Project of Hainan Province Scientific and Technical Plan(grant No.06701)
文摘Based on an interpretation and study of the satellite remote-sensing images of FY-2C thermal infrared 1st wave band （10.3-11.3 μm） designed in China, the authors found that there existed obvious and isolated satellite thermal infrared anomalies before the 5.12 Wenchuan Ms 8.0 Earthquake. These anomalies had the following characteristics： （1） The precursor appeared rather early： on March 18, 2008, i.e., 55 days before the earthquake, thermal infrared anomalies began to occur; （2） The anomalies experienced quite many and complex evolutionary stages： the satellite thermal infrared anomalies might be divided into five stages, whose manifestations were somewhat different from each other. The existence of so many anomaly stages was probably observed for the first time in numerous cases of satellite thermal infrared research on earthquakes; （3） Each stage lasted quite a long time, with the longest one spanning 13 days; （4） An evident geothermal anomaly gradient was distributed along the Longmen seismic fracture zone, and such a phenomenon might also be discovered for the first time in satellite thermal infrared earthquake research. This discovery is therefore of great guiding and instructive significance in the study of the earthquake occurrence itself and the trend of the postearthquake phenomena.
基金the Australian Coal Association Research Program(ACARP)for their invaluable support that enabled new research and development into longwall shearer automation
文摘Longwall mining continues to remain the most efficient method for underground coal recovery. A key aspect in achieving safe and productive longwall mining is to ensure that the shearer is always correctly positioned within the coal seam. At present, this machine positioning task is the role of longwall personnel who must simultaneously monitor the longwall coal face and the shearer's cutting drum position to infer the geological trends of the coal seam. This is a labour intensive task which has negative impacts on the consistency and quality of coal production. As a solution to this problem, this paper presents a sensing method to automatically track geological coal seam features on the longwall face, known as marker bands, using thermal infrared imaging. These non-visible marker bands are geological features that link strongly to the horizontal trends present in layered coal seams. Tracking these line-like features allows the generation of a vertical datum that can be used to maintain the shearer in a position for optimal coal extraction. Details on the theory of thermal infrared imaging are given, as well as practical aspects associated with machine-based implementation underground. The feature detection and tracking tasks are given with real measurements to demonstrate the efficacy of the approach. The outcome is important as it represents a new selective mining capability to help address a long-standing limitation in longwall mining operations.
基金Supported by the Key Laboratory of Mapping from Space of State Bureau of Surveying and Mapping（No.200815）, the Natural Science Foundation of China （NSFC 40371087, 40701119）, the Major State Basic Research Development Program of China （973 Program） （No. 2007CB714401）, the National High Technology Research and Development Program of China （863 Program） （No. 2007AA10Z201 ）.
文摘The multi-source data fusion methods are rarely involved in VNIR and thermal infrared remote sensing at present. Therefore, the potential advantages of the two kinds of data have not yet been adequately tapped, which results in low calculation precision of parameters related with land surface temperature. A new fusion method is put forward where the characteristics of the high spatial resolution of VNIR （visible and near infrared） data and the high temporal resolution of thermal infrared data are fully explored in this paper. Non-linear fusion is implemented to obtain the land surface temperature in high spatial resolution and the high temporal resolution between the land surface parameters estimated from VNIR data and the thermal infrared data by means of GA-SOFM （genetic algorithms ＆ self-organizing feature maps）-ANN （artificial neural net-work）. Finally, the method is verified by ASTER satellite data. The result shows that the method is simple and convenient and can rapidly capture land surface temperature distribution of higher resolution with high precision.
基金the research project of China Earthquake Administration—Earthquake Science and Technology Star Fire Plan(XH2018035Y)Seismic Regime Tracking Project of CEA(2020010410).
文摘Co-seismic gas leakage usually occurs on the edge of seismic faults in petroliferous basins,and it may have an impact on the local environment,such as the greenhouse effect,which can cause thermal infrared brightness anomalies.Using wavelet transform and power spectrum estimation methods,we processed brightness temperature data from the Chinese geostationary meteorological satellite FY-C/E.We report similarities between the co-seismic thermal infrared brightness(CTIB)anomalies before,during and after earthquakes that occurred at the edges of the Sichuan,Tarim,Qaidam,and Junggar basins surrounding the North and East of the Qinghai–Tibet Plateau in western China.Additionally,in each petroliferous basin,the area of a single CTIB anomaly accounted for 50%to 100%of the basin area,and the spatial distribution similarities in the CTIB anomalies existed before,during and after these earthquakes.To better interpret the similarities,we developed a basin warming effect model based on geological structures and topography.The model suggests that in a petroliferous basin with a subsurface gas reservoir,gas leakage could strengthen with the increasing stress before,during,and even after an earthquake.The accumulation of these gases,such as the greenhouse gases CH4 and CO2,results in the CTIB anomalies.In addition,we conclude that the CTIB anomalies are strengthened by the high mountains(altitude^5000 m)around the basins and the basins’independent climatic conditions.This work provides a new perspective from which to understand the CTIB anomalies in petroliferous basins surrounding the North and East of the Qinghai–Tibet Plateau.
基金Supported by the National Natural Science Foundation of China(No.41101503)the National Social Science Foundation of China(No.11&ZD161)Graduate Innovative Scientific Research Project of Chongqing Technology and Business University(No.yjscxx2014-052-29)
文摘According to the data characteristics of Landsat thematic mapper （TM） and MODIS, a new fu sion algorithm about thermal infrared data has been proposed in the article based on improving wave let reconstruction. Under the domain of neighborhood wavelet reconstruction, data of TM and MO DIS are divided into three layers using wavelet decomposition. The texture information of TM data is retained by fusing highfrequency information. The neighborhood correction coefficient method （NC CM） is set up based on the search neighborhood of a certain size to fuse lowfrequency information. Thermal infrared value of MODIS data is reduced to the space value of TM data by applying NCCM. The data with high spectrum, high spatial and high temporal resolution, are obtained through the al gorithm in the paper. Verification results show that the texture information of TM data and high spec tral information of MODIS data could be preserved well by the fusion algorithm. This article could provide technical support for high precision and fast extraction of the surface environment parame ters.
文摘This paper used the thermal infrared data of the satellite NOAA-AAVHRR of the north pat of North China (113°~119°E, 38°~42°N), and processed the remote sensing data through radiation adjustment, geometric adjust ment and so on by the software 'The Monitoring and Fast Process System of Earthquake Precursor Thermal Infra red Anomaly', inversed the each surface temperature. Some disturbances effect had been excluded, and thermal infrared temperature anomaly had been extracted by the picture difference method. The Zhangbei M_s=6.2 earth quake is used as the example in the paper, so that in the paper thermal infrared characteristics on time-space before earthquake and the relationship between the anomaly and the earthquake prediction have been summarized. Within more than ten days before the Zhangbei earthquake, the thermal infrared anomaly had emerged widely along Zhangjiakou-Bobal seismic belt, and the anomalous region seemed like a belt and it is also consistent with the tectonic background there; the anomaly expanded from the outside toward the earthquake focus, but the focus lay at the edge of the thermal infrared region. So it is possible to explore a new anomaly observation method for earthquake prediction by observing and studying the satellite thermal infrared anomaly before big earthquakes happen.
文摘The concept of stochastic resonance (SR) has been introduced into the analysis of satellite thermal infrared images. Six kinds of anomalous phenomena related to crustal movement were recognized in satellite thermal infrared images. Six diagnostic indicators for the prediction of global earthquakes with magnitude ≥6.0 and their quantitative evaluation standards have been established. The microscopic behavior of global crustal movement is successfully controlled by using satellite thermal infrared imagery, and the occurrence time and magnitude of over 80% of global strong earthquakes occurred since the foundation of the observation station have been successfully predicted. It is believed that the combination of satellite thermal infrared information with macroscopic anomalous phenomena will play an important role in earthquake hazard reduction.
基金National Natural Science Foundation of China (90202018).
文摘Aiming at two Dayao earthquakes with magnitude more than 6 occurred in 2003 in Yunnan Province, we analyzed and interpreted the NOAA satellite thermal infrared images of 1999, 2003 and 2004 in Chuandian region, and also calculated the annual variation of brightness temperature of the hot belt along Honghe fault to explore the formation cause of the high temperature belt and its relation to the earthquakes. The results show that the high temperature belt along Honghe fault is caused by geographic environment factors, such as water system and terrain. But the annual average brightness temperature of the belt in earthquake year of 2003 is clearly higher than that in no earthquake years of 1999 and 2004, this maybe indicates that the thermal activities of Honghe fault increase in earthquake years, and can cause the annual variation anomaly of brightness temperature. We can detect and monitor this thermal activities of Honghe fault before earthquake by analyzing and comparing the relative changes of thermal infrared brightness temperature of the hot belt in different years.
基金supported in part by the National Key Research and Development Program of China(No. 2018YFC0309104)the Construction System Science and Technology Project of Jiangsu Province (No.2021JH03)。
文摘Target detection in low light background is one of the main tasks of night patrol robots for airport terminal.However,if some algorithms can run on a robot platform with limited computing resources,it is difficult for these algorithms to ensure the detection accuracy of human body in the airport terminal. A novel thermal infrared salient human detection model combined with thermal features called TFSHD is proposed. The TFSHD model is still based on U-Net,but the decoder module structure and model lightweight have been redesigned. In order to improve the detection accuracy of the algorithm in complex scenes,a fusion module composed of thermal branch and saliency branch is added to the decoder of the TFSHD model. Furthermore,a predictive loss function that is more sensitive to high temperature regions of the image is designed. Additionally,for the sake of reducing the computing resource requirements of the algorithm,a model lightweight scheme that includes simplifying the encoder network structure and controlling the number of decoder channels is adopted. The experimental results on four data sets show that the proposed method can not only ensure high detection accuracy and robustness of the algorithm,but also meet the needs of real-time detection of patrol robots with detection speed above 40 f/s.
文摘Gait is an essential biomedical feature that distinguishes individuals through walking.This feature automatically stimulates the need for remote human recognition in security-sensitive visual monitoring applications.However,there is still a lack of sufficient accuracy of gait recognition at night,in addition to taking some critical factors that affect the performances of the recognition algorithm.Therefore,a novel approach is proposed to automatically identify individuals from thermal infrared(TIR)images according to their gaits captured at night.This approach uses a new night gait network(NGaitNet)based on similarity deep convolutional neural networks(CNNs)method to enhance gait recognition at night.First,the TIR image is represented via personal movements and enhanced body skeleton segments.Then,the state-space method with a Hough transform is used to extract gait features to obtain skeletal joints′angles.These features are trained to identify the most discriminating gait patterns that indicate a change in human identity.To verify the proposed method,the experimental results are performed by using learning and validation curves via being connected by the Visdom website.The proposed thermal infrared imaging night gait recognition(TIRNGaitNet)approach has achieved the highest gait recognition accuracy rates(99.5%,97.0%),especially under normal walking conditions on the Chinese Academy of Sciences Institute of Automation infrared night gait dataset(CASIA C)and Donghua University thermal infrared night gait database(DHU night gait dataset).On the same dataset,the results of the TIRNGaitNet approach provide the record scores of(98.0%,87.0%)under the slow walking condition and(94.0%,86.0%)for the quick walking condition.
基金supported by the Moroccan Ministry of Higher Education,Scientific Research,and Innovationthe Moroccan Digital Development Agency(DDA)+2 种基金the National Center for Scientific and Technical Research of Morocco(CNRST)through the Al-Khawarizmi projectthe MANAGEM groupMASCIR supporting this project.
文摘Rockfalls are among the frequent hazards in underground mines worldwide,requiring effective methods for detecting unstable rock blocks to ensure miners’and equipment’s safety.This study proposes a novel approach for identifying potential rockfall zones using infrared thermal imaging and image segmentation techniques.Infrared images of rock blocks were captured at the Draa Sfar deep underground mine in Morocco using the FLUKE TI401 PRO thermal camera.Two segmentation methods were applied to locate the potential unstable areas:the classical thresholding and the K-means clustering model.The results show that while thresholding allows a binary distinction between stable and unstable areas,K-means clustering is more accurate,especially when using multiple clusters to show different risk levels.The close match between the clustering masks of unstable blocks and their corresponding visible light images further validated this.The findings confirm that thermal image segmentation can serve as an alternative method for predicting rockfalls and monitoring geotechnical issues in underground mines.Underground operators worldwide can apply this approach to monitor rock mass stability.However,further research is recommended to enhance these results,particularly through deep learning-based segmentation and object detection models.
基金financial support of the Belgian National Fund for Scientific Research(FNRS)the Duesberg Foundation,and the University of Liège.
文摘Sleeping site selection is essential for understanding primate behavioral ecology and survival.Identifying where species sleep helps determine priority areas and critical resources for targeted conservation efforts.However,observing sleeping sites at night is challenging,especially for species sensitive to human disturbance.Thermal infrared imaging(TIR)with drones is increasingly used for detecting and counting primates,yet it has not been utilized to investigate ecological strategies.This study investigates the sleeping site selection of the Critically Endangered black-shanked douc langur(Pygathrix nigripes)in Cát Tiên National Park,Vietnam.Our aim is to assess the feasibility of using a TIR drone to test sleeping site selection strategies in non-nesting primates,specifically examining hypotheses related to predation avoidance and food proximity.Between January and April 2023,we conducted 120 drone flights along 22 transects(~1-km long)and identified 114 sleeping sites via thermal imaging.We established 116 forest structure plots along 29 transects in non-selected sites and 65 plots within douc langur sleeping sites.Our observations reveal that douc langurs selected tall and large trees that may provide protection against predators.Additionally,they selected sleeping sites with increased access to food,such as Afzelia xylocarpa,which serves as a preferred food source during the dry season.These results highlight the effective use of TIR drones for studying douc langur sleeping site selection with minimal disturbance.Besides offering valuable insights into habitat selection and behavioral ecology for conservation,TIR drones hold great promise for the noninvasive and long-term monitoring of large-bodied arboreal species.
